Customizing a barplot in matplotlib

Question

I want to customize my simple bar plot based on frequency of data. Context as follows:

I have a data set, where x-axis is referred to as var_change and y-axis as var_median and error-bars as var_error. The var_change and var_error are calculated at the bin size of 5-var_median. The code and the plot for these variables is shown below:

fig = plt.figure(figsize=(24,7))
ax = [plt.subplot(181)]
ax[i].barh(np.arange(0+2.5,99+2.5,5), var_change, alpha = 0.6, height = 5, 
           color='none', edgecolor='k', capsize=2.5, lw = 0.8)
ax[i].errorbar(var_change, np.arange(0+2.5,99+2.5,5), xerr = var_error, capsize=3, 
               fmt="r:o", ecolor = "black", alpha = 0.8)

I want to independently control both line-width (lw in barh), and alpha in errorbar, as well as color of individual bars in the bar plot below based on frequency of the data set. The frequency can be calculated using the code below:

#df_delta_pos is a data-frame
pos_count = []
for j in np.arange(0,99,5): 
    pos_count.append(df_delta_pos.where((df.var_median> TC_bins[j]) & 
                    (df.var_median<= TC_bins[j+5])).dropna()['var_change'].count())
#Here I would also normalize them if changing 'lw'. Code for normalization can be provided, if needed. 
#For now consider random numbers here.

The final plot should look something like below, but also with change in lw and alpha based on frequency.

Timo · Accepted Answer · 2020-10-29 09:25:45Z

1

Since you did not provide the data to the plot I cannot reproduce the figures. I try to answer your questions anyways.

Controls in barh: Taking a look at the documentation of barh you can pass to color and lw also a list/array which must be of the same length as the data.
Controls in errorbar: errorbar does not allow to specify a list for alpha. Your alternative is therefore to loop over each element in var_change and plot each element indiviually which then allows you to specify an alpha for each point.

edited Oct 29, 2020 at 9:25

answered Oct 28, 2020 at 18:21

Timo

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